Temporal Dynamics and Patterning of Meiofauna Community by Self-Organizing Artificial Neural Networks

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dc.contributor.authorLee, Woncheol
dc.contributor.authorSung-Ho, Kang
dc.contributor.authorMontagna, Paul A.
dc.contributor.authorInn-Sil, Kwak
dc.date.accessioned2023-05-30T17:39:39Z
dc.date.available2023-05-30T17:39:39Z
dc.date.issued2003-09-30
dc.description.abstractThe temporal dynamics of the meiofauna community in Marian Cove, King George Island were observed from January 22 to October 29 1996. Generally, 14 taxa of metazoan meiofauna were found. Nematodes were dominant comprising 90.12% of the community, harpacticoid 6.55%, and Kinorhynchs 1.54%. Meiofauna abundance increased monthly from January to May 1996, while varying in abundance after August 1996. Overall mean abundance of metazoan meiofauna was 2634ind./10cm2 during the study periods, which is about as high as that found in temperate regions. Nematodes were most abundant representing 2399ind./10cm2. Mean abundance of harpacticoids, including copepodite and nauplius was 131ind./10cm2 by kinorhynchs (26ind./10cm2). The overall abundance of other identified organisms was 31ind./10cm2 Other organisms consisted of a total of 11 taxa including Ostracoda (6ind./10cm2), Polycheata (7ind./10cm2), Oligochaeta (8ind./10cm2), and Bivalvia (6ind./10cm2). Additionally, protozoan Foraminifera occurred at the study area with a mean abundance of 263ind./10cm2. Foraminiferans were second in dominance to nematodes. The dominant taxa such as nematodes, harpacticoids, kinorhynchs and the other tua were trained and extensively scattered in the map through the Kohonen network. The temporal pattern of the community composition was most affected by the abundance dynamics of kinorhynchs and harpacticoids. The neural network model also allowed for simulation of data that was missing during two months of inclement weather. The lowest meiofauna abundance was found in August 1996 during winter. The seasonal changes were likely caused by temperature and salinity changes as a result of meltwater runoff, and the physical impact by passing icebergs.en_US
dc.identifier.citationLee, W., Kang, S.-H. Kang, P.A. Montagna, and I.-S. Kwak. 2003. Temporal dynamics and patterning of meiofauna community by self-organizing artificial neural networks. Ocean and Polar Research 25:237-247. doi: 10.4217/OPR.2003.25.3.237en_US
dc.identifier.urihttps://hdl.handle.net/1969.6/96366
dc.language.isoen_USen_US
dc.publisherOcean and Polar Researchen_US
dc.titleTemporal Dynamics and Patterning of Meiofauna Community by Self-Organizing Artificial Neural Networksen_US
dc.typeArticleen_US

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